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This research aims at indulging a consistent image of how Digitalization Capabilities (DC) demonstrates an impact on Sustainable Auditing Ecosystem (SAE) within public sector organizations (PSOs) in developing countries, especial in an emerging market, and gives insights regarding to divergent impacts of the interconnection between DC and SAE moderated by different levels of Accountants' Digital Intelligence (ADI). The state-of-the-art structural equation modelling (SEM) was employed to statistically analyze the survey data collected from self-administered questionnaire distributed to a convenient sample of 323 respondents. Additionally, multi-group analysis (MGA) was implemented to explore the heterogeneity of data and examined substance of the difference in the parameters caused by the moderating variable. The obtained results advocated that it was paramount for PSOs to increase DC for SAE formulation. The MGA findings highlighted a statistically significant difference in the impacts of DC on SAE between various levels of ADI. The insights acquired from final model emerged as a foundation which might buttress policymakers and PSOs' practitioners in initiatives development pertaining to digitalization for SAE formulation.
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Medical homogenization in multi-campus hospital plays an essential role in leveraging the advantages of public hospitals, promoting the expansion of high-quality medical resources and balancing regional layout. The Second Affiliated Hospital Zhejiang University School of Medicine deeply used digital intelligence technology to build a new integrated mobile health service system consisting of internet hospital and 5G intelligent applications, which empowered medical efficiency in multi-campus hospital. This system broke the limitations of inconsistent medical resources, unbalanced discipline layout, and insufficient information connectivity in the construction of multi-campus hospitals, and achieved remarkable results in practice. It could provide reference for the multi-campus construction of other large public hospitals.
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【Objective】 To explore the effect of online and offline collaborative and integrated mode (Internet + blood donation souvenirs), and develop diversified scientific ways of caring for voluntary blood donors in combination with the potential expectation of the target population, ao as to recruit and retain more blood donors. 【Methods】 A total of 4 000 blood donors from Yichang Central Blood Station from January 1 to June 30, 2022 were selected, and they could collect souvenirs from online and offline. The intelligent platform V9.5 of modern blood station management information system of Qiao Technology was used to classify the data of online and offline souvenir distribution, and digital intelligent comparison and analysis on age, occupation, education, type (first-time blood donors or repeat blood donors), region (main urban districts of Yichang and other counties and suburban districts) and gender were carried out. 【Results】 A total of 1 400 blood donors chose online souvenirs, who were mainly under 25 years old, students, female, college education or above, urban areas and regular donors; 2 600 chose offline souvenirs, who were mainly over 25 years old, male, junior college degree or below, occupations other than students (medical workers, educators, etc.), counties and suburban districts, and first-time blood donors. The collaborative and integrated mode of the two distribution methods were complementary and had a good incentive effect on blood donor recruitment. 【Conclusion】 The online and offline collaborative and integrated mode demonstrates a good effect and meets the needs of different population. Digital intelligence system is helpful to develop diversified and scientific ways of caring for voluntary blood donors, recruit and retain more blood donors, achieve high-quality development of blood collection and supply, therefore guarantee the increasing demand for clinical blood use.
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Digital intelligent hepatobiliary surgery has evolved over decades.It has experienced an evolution course from digital virtual human technology to the establishment of a quality-controlled and homogeneous three-dimensional visualization system for precision diagnosis and treatment of diseases, from three-dimensional visualization to the clinical transformation of digital intelligent technology and changes in the diagnosis and treatment model, from empirical diagnosis of diseases to the application of deep learning for the intelligent diagnosis and treatment of diseases, from empirical surgery to real-time multi-modal image guidance during surgery, and from the morphological diagnosis of tumors to accurate diagnosis from molecular imaging.During the whole process, only through continuous innovation in research, theory and technology can the "life" of digital intelligent surgery be endowed with new vitality.In the future, the definition of tumor boundary from the molecular and cellular levels and the early diagnosis and treatment of liver tumor through the functional visualization of key molecules will have significant clinical value for changing the prognosis of liver cancer.In addition, in order to realize intelligent navigation for hepatectomy and break through the technical bottleneck, it is of great clinical significance to develop an intelligent robot real-time navigation hepatectomy system with automatic navigation technology, machine learning intelligent planning technology and multimodal image fusion technology.This provides unprecedented opportunities and challenges for the development of digital intelligent hepatobiliary surgery.
Assuntos
Hepatectomia/métodos , Imageamento Tridimensional/métodos , Neoplasias Hepáticas/cirurgia , Inteligência Artificial , Humanos , Neoplasias Hepáticas/diagnóstico por imagemRESUMO
Digital intelligent hepatobiliary surgery has evolved over decades.It has experienced an evolution course from digital virtual human technology to the establishment of a quality-controlled and homogeneous three-dimensional visualization system for precision diagnosis and treatment of diseases, from three-dimensional visualization to the clinical transformation of digital intelligent technology and changes in the diagnosis and treatment model, from empirical diagnosis of diseases to the application of deep learning for the intelligent diagnosis and treatment of diseases, from empirical surgery to real-time multi-modal image guidance during surgery, and from the morphological diagnosis of tumors to accurate diagnosis from molecular imaging.During the whole process, only through continuous innovation in research, theory and technology can the "life" of digital intelligent surgery be endowed with new vitality.In the future, the definition of tumor boundary from the molecular and cellular levels and the early diagnosis and treatment of liver tumor through the functional visualization of key molecules will have significant clinical value for changing the prognosis of liver cancer.In addition, in order to realize intelligent navigation for hepatectomy and break through the technical bottleneck, it is of great clinical significance to develop an intelligent robot real-time navigation hepatectomy system with automatic navigation technology, machine learning intelligent planning technology and multimodal image fusion technology.This provides unprecedented opportunities and challenges for the development of digital intelligent hepatobiliary surgery.
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Digital intelligent diagnostic and treatment technology refers to a novel technology which is based by associating digitalized and intelligent high-tech with modern science to form a multi-knowledge and multi-disciplinary domain; it includes three-dimensional visualization,3 D printing,molecular fluorescence imaging,mixed reality,photoacoustic imaging,artificial intelligence-radiomis and real-time multimodal image surgical navigation.It plays a significant role in precision diagnosis,preoperative planning and intraoperative navigation of diseases.The authors' team,combining digital intelligent technology with the actual vascular distribution of patients,has been committed to the realization of individualized liver segmentation,volume calculation,simulation surgery,preoperative planning,mixed reality,tumor boundary definition and real-time image fusion for navigation in liver surgery.The research results were applied clinically,and achieved anatomical,functional,and radical hepatectomy for liver tumors.
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The maturity level of the digital transformation in health care ecosystems is heavily depending on human factors. Primarily the digital intelligence of the human beings - e.g. medical or nursing staff - should be taken seriously in the transformation processes. To derive sustainable strategies in a holistic manner an innovative, multi-dimensionaland human centred socio-economic capability model had to be developed and applied. By the use of our model health care ecosystems can be analysed, scored and benchmarked successfully. Furthermore, each ecosystems' digital intelligence based on their employees can be derived holistically from our four scoring scopes.
